GENERATIVE GRAMMAR MODELS FOR EFFECTIVE PROMOTION AND ADVERTISING

    公开(公告)号:US20200242307A1

    公开(公告)日:2020-07-30

    申请号:US16845767

    申请日:2020-04-10

    Applicant: eBay Inc.

    Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. A generative grammar model defining a message structure of requested message is accessed. The message structure includes a plurality of lexical slots. The generative grammar model includes a corpus of source data to populate each lexical slot in the plurality of lexical slots, and a grammatical constraint for each lexical slot in the plurality of lexical slots. A message is generated in accordance with the generative grammar model and the message is published.

    Generative grammar models for effective promotion and advertising

    公开(公告)号:US11321539B2

    公开(公告)日:2022-05-03

    申请号:US16845767

    申请日:2020-04-10

    Applicant: eBay Inc.

    Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating advertisement messages using generative grammar models is presented. A generative grammar model defining a message structure of requested message is accessed. The message structure includes a plurality of lexical slots. The generative grammar model includes a corpus of source data to populate each lexical slot in the plurality of lexical slots to generate an advertisement message for a product listing. An advertisement message is generated in accordance with the generative grammar model and the message is published. The advertisement message for the product listing is then transmitted to a client device.

    Predicting purchase session behavior using the shopping funnel model stages

    公开(公告)号:US10185972B2

    公开(公告)日:2019-01-22

    申请号:US14290637

    申请日:2014-05-29

    Applicant: eBay Inc.

    Abstract: A user activity detection engine monitors user activity during user sessions on a publication system, and detects a change in the level of the activity of the user that predicts that the user is about to execute a transaction. The change may be an increase in the level of activity. When the user activity detection engine detects such a change, the system may make an intervention to provide personalized marketing content for display to the user in an effort to improve the probability that the user will execute a transaction, and/or also to motive the user to execute the transaction on the system site instead of moving to a competitor site in search of a different transaction.

    MACHINE GENERATED RECOMMENDATION AND NOTIFICATION MODELS
    7.
    发明申请
    MACHINE GENERATED RECOMMENDATION AND NOTIFICATION MODELS 审中-公开
    机器生成推荐和通报模型

    公开(公告)号:US20160086206A1

    公开(公告)日:2016-03-24

    申请号:US14861741

    申请日:2015-09-22

    Applicant: eBay Inc.

    Abstract: Systems and methods are presented for matching a buyer and a seller on a market place system and generating calibrated user profiles. In one such system a plurality of subjective estimations of value is received. The subjective estimations of value are a measure between a predetermined minimum value and a predetermined maximum value. A user profile is generated. A plurality of user actions corresponding to the plurality of subjective estimations of value is received. The user profile is calibrated based on the plurality of user actions.

    Abstract translation: 提供了系统和方法,用于在市场位置系统上匹配买方和卖方,并生成校准的用户简档。 在一个这样的系统中,接收到多个主观估价值。 值的主观估计是预定最小值和预定最大值之间的量度。 生成用户配置文件。 接收与多个主观估计值对应的多个用户动作。 基于多个用户动作来校准用户简档。

    Generative grammar models for effective promotion and advertising

    公开(公告)号:US10650104B2

    公开(公告)日:2020-05-12

    申请号:US16040788

    申请日:2018-07-20

    Applicant: eBay Inc.

    Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. A generative grammar model defining a message structure of requested message is accessed. The message structure includes a plurality of lexical slots. The generative grammar model includes a corpus of source data to populate each lexical slot in the plurality of lexical slots, and a grammatical constraint for each lexical slot in the plurality of lexical slots. A message is generated in accordance with the generative grammar model and the message is published.

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